Personnel Attitudes toward the Implementation of AI Solutions: A Pilot Study in the Transport Sector
EDN: DNSKNX
Abstract
This article is devoted to analyzing the attitude of personnel in a transport enterprise towards the implementation of artificial intelligence (AI) for monitoring operator states. Drawing on the diffusion of innovations, technology acceptance and change management frameworks, it hypothesises that acceptance is shaped not only by technical features but also by psychological, socio cultural and communicative factors.
The empirical foundation includes two sequentially connected stages: prototype testing in a simulation environment and field trials during real operations.
The method involved semi-structured interviews with 20 employees (purposeful selection by work experience and age), followed by thematic and frequency analysis; to compare subjective “before/after” assessments, a nonparametric test of differences was applied. The findings show that the acceptance of an AI solution is determined not only by technical parameters but also by psychological, sociocultural, and communicative factors: perceptions of “observability” and control, algorithmic transparency, ergonomics, and staff participation in refinement.
Based on the data, managerial mechanisms for reducing resistance are proposed: extended communication and explainability, user involvement in iterative design, targeted training, and a structured feedback protocol. Thus, an empirically grounded model of guided AI implementation in high-responsibility organizations is proposed, relevant for the practices of state and municipal governance.
About the Authors
A. B. Demarev
Lobachevsky University
Russian Federation
Russian Federation
Nizhny Novgorod
I. E. Petrova
Lobachevsky University
Russian Federation
Russian Federation
Nizhny Novgorod
References
1. Bortsov Yu. S. Sociocultural barriers in the processes of informatization of education // Integration of Education [Integratsiya obrazovaniya]. 2014. N 3. P. 15–21. EDN TPMUIZ. (In Russ.).
2. Bochegov M. A., Savchenko T. O. Implementation of AI technologies in transport and logistics systems // Problems of Science [Problemy nauki]. 2024. Vol. 85. N 4. P. 22–25. EDN CZBDMU. (In Russ.).
3. Glukhov A. P. The impact of resistance to digitalization on the diffusion of digital platform solutions // Tomsk State University Journal. Economics [Vestnik Tomskogo gosudarstvennogo universiteta. Ekonomika]. 2019. Vol. 48. P. 57–82. DOI 10.17223/19988648/48/6. EDN NRSNTZ. (In Russ.).
4. Dashkov A. A., Nesterova Yu. O. Building trust in the use of artificial intelligence // E-Management. 2021. Vol. 4, N 2. P. 28–36. DOI 10.26425/2658-3445-2021-4-2-28-36. EDN TCJOUX. (In Russ.).
5. Ermolaev V. V., Chetverikova A. I., Vorontsova Yu., Nasonova D. K. Features of modern tools for diagnosing attention and work capacity of drivers // Journal of Modern Foreign Psychology [Sovremennaya zarubezhnaya psikhologiya]. 2023. Vol. 12. N 1. P. 56–66. DOI 10.17759/ jmfp.2023120106. EDN DFXNQR. (In Russ.).
6. Mkrtichyan G. A., Isaeva O. M. Reasons for personnel resistance to organizational changes: the view of managers as change agents // Organizational Psychology [Organizatsionnaya psikhologiya]. 2015. Vol. 5. N 1. P. 22–33. EDN TOPUKB. (In Russ.).
7. Shirokova E. N. Reducing resistance to changes in railway enterprises in the context of reforms. Science and Progress of Transport // Bulletin of Dnipropetrovsk National University of Railway Transport [Vestnik Dnepropetrovskogo natsionalnogo universiteta zheleznodorozhnogo transporta]. 2013. Vol. 45. N 3. P. 7–12. EDN RYFRLZ. (In Russ.).
8. Ajzen I. The theory of planned behavior // Organizational Behavior and Human Decision Processes. 1991. Vol. 50. N 2. P. 179–211.
9. Albadawi Y., Takruri M., Awad M. A Review of Recent Developments in Driver Drowsiness Detection Systems // Sensors. 2022. Vol. 22. N 5. Art. 2069.
10. Chen J. Y. C., Barnes M. J. Human-agent teaming for multirobot control: a review of the human factors issues // IEEE Trans. Hum. Mach. Syst. 2014. Vol. 44. P. 13–29.
11. Ciani L., Guidi G., Patrizi G. Human reliability in railway engineering: Literature review and bibliometric analysis of the last two decades // Safety Science. 2022. Vol. 151. Art. 105755.
12. Cummings T. G., Worley C. G. Organization Development and Change. 10th ed. Boston: Cengage Learning, 2014.
13. Davis F. D. Perceived usefulness, perceived ease of use, and user acceptance of information technology // MIS Quarterly. 1989. Vol. 13. N 3. P. 319–340.
14. Endsley M. R. Toward a theory of situation awareness in dynamic systems // Human Factors. 1995. Vol. 37. N 1. P. 32–64.
15. Kline S. J., Rosenberg N. An overview of innovation // The Positive Sum Strategy: Harnessing Technology for Economic Growth. Washington, DC: National Academy Press, 1986. P. 275–305.
16. Kotter J. P. Leading Change. Boston: Harvard Business School Press, 1996.
17. Lewin K. Frontiers in group dynamics: Concept, method and reality in social science; social equilibria and social change // Human Relations. 1947. Vol. 1. P. 5–41.
18. Orlikowski W. J., Iacono C. S. Research commentary: Desperately seeking the “IT” in IT research — A call to theorizing the IT artifact // Information Systems Research. 2001. Vol. 12. N 2. P. 121–134.
19. Parasuraman A., Colby C. L. Techno-Ready Marketing: How and Why Your Customers Adopt Technology. New York: Free Press, 2001.
20. Petter S., DeLone W., McLean E. Measuring information systems success: Models, dimensions, measures, and interrelationships // European Journal of Information Systems. 2008. Vol. 17. N 3. P. 236–263.
21. Preece J., Rogers Y., Sharp H. Interaction Design: Beyond Human-Computer Interaction. 4th ed. Chichester: Wiley, 2015.
22. Proctor R. W., Van Zandt T. Human Factors in Simple and Complex Systems. 3rd ed. Boca Raton: CRC Press, 2018.
23. Rogers E. M. Diffusion of Innovations. 5th ed. New York: Free Press, 2003.
24. Van de Ven A. H., Poole M. S. Explaining development and change in organizations // Academy of Management Review. 1995. Vol. 20. N 3. P. 510–540.
25. Venkatesh V., Davis F. D. A theoretical extension of the technology acceptance model: Four longitudinal field studies // Management Science. 2000. Vol. 46. N 2. P. 186–204.
26. Warkentin M., Gefen D., Pavlou P. A., Rose G. M. Encouraging citizen adoption of e-government by building trust // Electronic Markets. 2002. Vol. 12. N 3. P. 157–162.
27. Yang G., Ridgeway C., Miller A., Sarkar A. Comprehensive assessment of artificial intelligence tools for driver monitoring and analyzing safety critical events in vehicles // Sensors. 2024. Vol. 24. N 8. Art. 2478.
28. Yoo Y., Henfridsson O., Lyytinen K. Research commentary—the new organizing logic of digital innovation: An agenda for information systems research // Information Systems Research. 2010. Vol. 21. N 4. P. 724–735.
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For citations:
Demarev A.B., Petrova I.E. Personnel Attitudes toward the Implementation of AI Solutions: A Pilot Study in the Transport Sector. Administrative Consulting. 2025;(5):205–214. (In Russ.) EDN: DNSKNX
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